docs: def sg_summary_gradient(tensor, gradient, prefix=None, name=None):
      r"""Register `tensor` to summary report as `gradient`
  
      Args:
        tensor: A `Tensor` to log as gradient
        gradient: A 0-D `Tensor`. A gradient to log
        prefix: A `string`. A prefix to display in the tensor board web UI.
        name: A `string`. A name to display in the tensor board web UI.
  
      Returns:
          None
      """
      # defaults
      prefix = '' if prefix is None else prefix + '/'
      # summary name
      name = prefix + _pretty_name(tensor) if name is None else prefix + name
      # summary statistics
      # noinspection PyBroadException
      _scalar(name + '/grad', tf.reduce_mean(tf.abs(gradient)))
      _histogram(name + '/grad-h', tf.abs(gradient))